王垚 钮心毅 宋小冬

Wang Yao, Niu Xinyi, Song Xiaodong

关键词：“ 流空间”；“流”数据；区域研究；空间结构；空间相互作用

Keywords：Space of Flow; Data of Flow; Regional Studies; Spatial Structure; Spatial Interaction

摘要：

通过对国外近几年关于“流空间”视角下区域空间结构研究的文献梳理，发现研究领域集中在区域中心性测度方法，从功能性角度识别多中心空间结构，传统腹地和网络腹地的划分以及中心地理论、城市网络理论和引力模型等理论验证四个方面。四个方面的研究深入都与“流”类型及其测度方法演变密切相关。不同类型的“流”数据在区域空间结构研究中起到了重要推动作用，尤其是手机信令数据、互联网数据、手机通话数据等大数据能更好地反映区域城市之间的空间相互作用，为“流空间”视角下的区域空间研究提供了新的机遇。以“物流”数据测度的“流”分析、整合大数据和传统数据、进一步认识不同类型“流”差异及适用环境将是未来的研究方向。

Abstract：

Based on the review of recent literatures of regional spatial structure studies in the perspective of space of flow, this paper finds most researches focused on four areas: measurement of regional centrality, identification of polycentric spatial structure in functional perspective, delimitation of traditional hinterland and network hinterland, as well as the verification of central place theory, network theory and gravity model. The studies in these four areas are all closely related to the evolution of the types of flow and their measurement methods. Different types of data of flow play important roles in the study of regional spatial structure. Big data especially such as mobile phone signaling data, internet data and mobile phone call record data can better reflect the interactions between the regional city spaces. The emerging big data provides new opportunities for the research of regional spatial structure in the perspective of space of flow. Results reported in this paper indicate three future research directions: flow analysis of logistics data, integration of big data and traditional data, further understanding of the different flow types and its applicability.

王垚，同济大学建筑与城市规划学院，博士研究生。245540789@qq.com
钮心毅（通信作者），同济大学建筑与城市规划学院，高密度人居环境生态与节能教育部重点实验室，副教授，博士生导师。niuxinyi@tongji.edu.cn
宋小冬，同济大学建筑与城市规划学院，高密度人居环境生态与节能教育部重点实验室，教授，博士生导师

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